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Position Summary: The UM6P Vanguard Center & The School of Applied Sciences & Engineering at UM6P invite applications for the position of Research Scientist in Data Science & Machine Learning
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and Machine Learning, with a focus on studying geometric structures in data and models and how to leverage such structure for the design of efficient machine learning algorithms with provable guarantees
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of statistical signal processing, inference, machine learning and dynamical systems theory to develop new semi-analtyical filtering approaches for state and parameter estimation to infer neurophysiological
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the area of efficient and interpretable machine learning systems. The successful candidate will work on projects involving ensemble learning, large-scale data analytics, and high-performance model design
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Massachusetts Institute of Technology | Cambridge, Massachusetts | United States | about 5 hours ago
how circuit structure supports computation. Will lead research on one or more of the following areas: Automated proofreading & annotation at scale: Machine learning approaches for error detection, human
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research focuses on developing and applying computational frameworks—including machine learning, nonlinear dynamical systems, and hybrid physics-integrated machine learning models—to predict, analyze
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models (transformers, diffusion models, GANs, etc.) * Quantum machine learning or tensor networks or quantum algorithms * Theoretical or applied aspects of quantum information Website for additional job
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(Mandatory): Machine Learning Statistical Modeling Data Visualization Academic Writing Languages (Mandatory): English: IELTS 7.0 or higher LanguagesENGLISHLevelExcellent Research FieldComputer science
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phenotypes have been observed across developmental systems or model organisms. Build and apply machine learning and AI models (e.g., generative or trajectory-based models, foundation models) to identify and
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Science, Machine Learning, Computer Science, Applied Statistics, or a related field. Demonstrated expertise in supervised/unsupervised learning, deep learning, and data-driven modeling. Proficiency in